Relationship between psychological characteristics, personality traits, and training on performance in a neonatal resuscitation scenario: A machine learning based analysis.

Background: In life-threatening emergency events, prompt decision-making and accurate reactions are essential for saving a human's life. Some of these skills can be improved by regular simulation trainings. However, besides these factors, individual characteristics may play a significant role in the patients' outcome after a resuscitation event. This study aimed to differentiate personality characteristics of team members who take responsibility for their actions, contextualizing the effect of training on resuscitation performance. Methods: Six hundred and two third-year medical students were asked to answer psychological and personality questionnaires. Fifty-five of them performed in a neonatal simulation resuscitation scenario. To assess participants' performances in the NLS scenario, we used a scenario-based designed NLS checklist. A machine learning design was utilized to better understand the interaction of psychological characteristics and training. The first model aimed to understand how to differentiate between people who take responsibility for their actions vs. those who do not. In a second model, the goal was to understand the relevance of training by contextualizing the effect of training to other important psychological and personality characteristics like locus of control, anxiety, emotion regulation, openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism. Results: No statistically significant differences were found for psychological characteristics between the training group and the no training group. However, as expected, differences were noted in favor of the training group for performance and within gender for psychological characteristics. When correcting for all these information in a model, anxiety and gender were the most important factors associated with taking responsibility for an action, while training was the only relevant factor in explaining performance during a neonatal resuscitation scenario. Conclusion: Training had a significantly stronger effect on performance in medical students in a neonatal resuscitation scenario than individual characteristics such as demographics, personality, and trait anxiety.

No time for drifting: Comparing performance and applicability of signal detrending algorithms for real-time fMRI.

As a consequence of recent technological advances in the field of functional magnetic resonance imaging (fMRI), results can now be made available in real-time. This allows for novel applications such as online quality assurance of the acquisition, intra-operative fMRI, brain-computer-interfaces, and neurofeedback. To that aim, signal processing algorithms for real-time fMRI must reliably correct signal contaminations due to physiological noise, head motion, and scanner drift. The aim of this study was to compare performance of the commonly used online detrending algorithms exponential moving average (EMA), incremental general linear model (iGLM) and sliding window iGLM (iGLMwindow). For comparison, we also included offline detrending algorithms (i.e., MATLAB's and SPM8's native detrending functions). Additionally, we optimized the EMA control parameter, by assessing the algorithm's performance on a simulated data set with an exhaustive set of realistic experimental design parameters. First, we optimized the free parameters of the online and offline detrending algorithms. Next, using simulated data, we systematically compared the performance of the algorithms with respect to varying levels of Gaussian and colored noise, linear and non-linear drifts, spikes, and step function artifacts. Additionally, using in vivo data from an actual rt-fMRI experiment, we validated our results in a post hoc offline comparison of the different detrending algorithms. Quantitative measures show that all algorithms perform well, even though they are differently affected by the different artifact types. The iGLM approach outperforms the other online algorithms and achieves online detrending performance that is as good as that of offline procedures. These results may guide developers and users of real-time fMRI analyses tools to best account for the problem of signal drifts in real-time fMRI.

Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training.

Recent advances in neurofeedback based on real-time functional magnetic resonance imaging (fMRI) allow for learning to control spatially localized brain activity in the range of millimeters across the entire brain. Real-time fMRI neurofeedback studies have demonstrated the feasibility of self-regulating activation in specific areas that are involved in a variety of functions, such as perception, motor control, language, and emotional processing. In most of these previous studies, participants trained to control activity within one region of interest (ROI). In the present study, we extended the neurofeedback approach by now training healthy participants to control the interhemispheric balance between their left and right visual cortices. This was accomplished by providing feedback based on the difference in activity between a target visual ROI and the corresponding homologue region in the opposite hemisphere. Eight out of 14 participants learned to control the differential feedback signal over the course of 3 neurofeedback training sessions spread over 3 days, i.e., they produced consistent increases in the visual target ROI relative to the opposite visual cortex. Those who learned to control the differential feedback signal were subsequently also able to exert that control in the absence of neurofeedback. Such learning to voluntarily control the balance between cortical areas of the two hemispheres might offer promising rehabilitation approaches for neurological or psychiatric conditions associated with pathological asymmetries in brain activity patterns, such as hemispatial neglect, dyslexia, or mood disorders.

Real-time fMRI neurofeedback: progress and challenges.

In February of 2012, the first international conference on real time functional magnetic resonance imaging (rtfMRI) neurofeedback was held at the Swiss Federal Institute of Technology Zurich (ETHZ), Switzerland. This review summarizes progress in the field, introduces current debates, elucidates open questions, and offers viewpoints derived from the conference. The review offers perspectives on study design, scientific and clinical applications, rtfMRI learning mechanisms and future outlook.

Illusion effects on grasping are temporally constant not dynamic.

The authors tested whether the effects of the Ebbinghaus illusion on grasping are corrected during late phases of the movement. Surprisingly, the grasp aperture was corrected neither under no-vision (N = 52) nor under full-vision (N = 48) conditions. The authors show that previous reports of a correction (e.g., S. Glover & P. Dixon, 2002a) are due to 2 artifacts: (a) inclusion of time points at which the target object was already touched and (b) erroneous statistics. This removes the central evidence on which S. Glover and P. Dixon's (2001a) planning-control model of action is based. In addition, the authors' results can help to refine more classic notions of motor control (e.g., R. Woodworth, 1899). In consequence, the authors reject S. Glover and P. Dixon's (2001a) planning-control model but not classic online-control theories.

Antiplatelet effects of ticlopidine are reduced in experimental hypercholesterolemia.

This study determines the antiplatelet effects of oral ticlopidine (100 mg/kg x day) in experimental hypercholesterolemia. Rabbits were fed either a standard diet or a cholesterol-enriched diet (0.5% for 3 months, 1% for 1 month). In normocholesterolemic controls ADP-, but not collagen-induced platelet aggregation was inhibited by ticlopidine treatment. This was accompanied by a significantly enhanced inhibition of ADP-induced platelet aggregation and stimulation of cyclic AMP accumulation by iloprost. Hypercholesterolemia considerably attenuated the inhibition of ADP-induced aggregation by ticlopidine but did not change its effect on the iloprost-induced inhibition of platelet function and cyclic AMP formation. ADP-induced platelet-derived thromboxane formation was considerably greater in hypercholesterolemic rabbits and not reduced by ticlopidine. Ticlopidine did also not significantly influence the extent and severity of atherosclerotic plaque formation although a tendency for improvement was observed in a subgroup of animals. The data suggest that hypercholesterolemia attenuates the inhibitory effect of ticlopidine on ADP-induced platelet aggregation. This might be related to the stimulation of thromboxane formation by ADP in hypercholesterolemia. The maintained protection from ADP-induced inhibition of cAMP accumulation suggests a minor role of this mechanism in the progression of hypercholesterolemia-induced vessel disease in this model.